What Biased estimator is
A biased estimator is a statistic used to estimate a population parameter that systematically overestimates or underestimates the parameter of interest. A biased estimator is not necessarily incorrect, but it can lead to incorrect conclusions if it is not properly adjusted or corrected.
Steps for identifying a biased estimator:
- Collect data relevant to the population parameter to be estimated.
- Calculate the statistic of interest.
- Compare the calculated statistic to the true value of the parameter.
- If the calculated statistic systematically overestimates or underestimates the true value, the statistic is biased.
- Adjust or correct the statistic to account for the bias.
Examples
- Using a sample size that is too small to accurately represent the population.
- Using a sample that is not representative of the population (e.g. sampling only a certain subset of the population).
- Using an incorrect method of estimation or calculation.
- Not considering all the factors when making an estimation.
- Using outdated or inaccurate data.
- Making estimations based on personal or subjective opinions.